Multi-Object Grasping in the Plane
Not on the map. Why?
Abstract (arXiv)
We consider a novel problem where multiple rigid convex polygonal objects rest in randomly placed positions and orientations on a planar surface visible from an overhead camera. The objective is to efficiently grasp and transport all objects into a bin using multi-object push-grasps, where multiple objects are pushed together to facilitate multi-object grasping. We provide necessary conditions for frictionless multi-object push-grasps and apply these to filter inadmissible grasps in a novel multi-object grasp planner. We find that our planner is 19 times faster than a Mujoco simulator baseline. We also propose a picking algorithm that uses both single- and multi-object grasps to pick objects. In physical grasping experiments comparing performance with a single-object picking baseline, we find that the frictionless multi-object grasping system achieves 13.6% higher grasp success and is 59.9% faster, from 212 PPH to 340 PPH. See urlhttps://sites.google.com/view/multi-object-grasping for videos and code.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 13 of its 36 references that are in the map. First posted on arXiv 1 Jun 2022.
Builds on
13 of 36 references.
References · 13
- 2013Data-Driven Grasp Synthesis - A Surveycited by 106
- 2020Occlusion-Aware Search for Object Retrieval in Cluttercited by 12
- 2021Collision-Aware Target-Driven Object Grasping in Constrained Environmentscited by 11
- 2021Multi-Object Grasping -- Estimating the Number of Objects in a Robotic Graspcited by 5
- 2020GOMP: Grasp-Optimized Motion Planning for Bin Pickingcited by 4
- 2018Pushing Fast and Slow: Task-Adaptive Planning for Non-prehensile Manipulation Under Uncertaintycited by 3
- 2018Real-Time Online Re-Planning for Grasping Under Clutter and Uncertaintycited by 3
- 2018O2A: One-shot Observational learning with Action vectorscited by 3
- 2021Multi-Object Grasping -- Generating Efficient Robotic Picking and Transferring Policycited by 3
- 2019Combining Coarse and Fine Physics for Manipulation using Parallel-in-Time Integrationcited by 2
- 2020Human-like Planning for Reaching in Cluttered Environmentscited by 2
- 2021Robust Physics-Based Manipulation by Interleaving Open and Closed-Loop Executioncited by 2
1 more
Built on by
Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 2.
5 papers.
- 2024A Survey of Embodied Learning for Object-Centric Robotic Manipulationcited by 35
- 2023Grasp Multiple Objects with One Handcited by 18
- 2022Learning to Efficiently Plan Robust Frictional Multi-Object Graspscited by 5
- 2025Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generationcited by 3
- 2025Learning to Push, Group, and Grasp: A Diffusion Policy Approach for Multi-Object Deliverycited by 0
- 2025Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generation28 Mar 2025
- 2025Learning to Push, Group, and Grasp: A Diffusion Policy Approach for Multi-Object Delivery12 Feb 2025
- 2024A Survey of Embodied Learning for Object-Centric Robotic Manipulation21 Aug 2024
- 2023Grasp Multiple Objects with One Hand24 Oct 2023
- 2022Learning to Efficiently Plan Robust Frictional Multi-Object Grasps13 Oct 2022